Stein’s method and zero bias transformation for CDO tranche pricing

We propose an original approximation method, which is based on Stein’s method and the zero bias transformation, to calculate CDO tranches in a general factor framework. We establish first-order correction terms for the Gaussian and the Poisson approximations respectively and we estimate the approximation errors. The application to the CDO pricing consists of combining the two approximations. This work is partially supported by Fondation de risque.     

结构等应力线的一种有效绘制方法

提出一种基于高斯点应力绘制受载结构等应力图的有效而简单的方法。直接根据有限元计算求得的高斯点应力值 ,连续在结构边界高斯点和内部共用相邻高斯点中搜索等应力点 ,通过 .SCR命令组文件 ,在 Auto CAD中自动生成等应力图 ,图形清晰 ,效率较高。在不同的加载等级下分别绘制这些等应力图 ,可直观地观察和分析结构应力场的分布和变化情况     

RISK‐REWARD OPTIMIZATION WITH DISCRETE‐TIME COHERENT RISK

We solve the risk‐reward optimization problem in the discrete‐time setting, the reward being measured as the expected Profit and Loss and the risk being measured by a dynamic coherent risk measure.     

Generalized Hyperbolic Diffusion Processes with Applications in Finance

A special class of diffusion processes, the generalized hyperbolic diffusion processes, is introduced. As a byproduct we present a technique for the construction of one-dimensional ergodic diffusion processes with a predetermined stationary density. We specifically study the application of this new type of diffusion process to financial data, especially U.S. stock prices. It is seen that in addition to confirming stylized features of the financial market, a key explanation concerning "thick-"tailed log returns is provided.     

A new approach to modeling co-movement of international equity markets: evidence of unconditional copula-based simulation of tail dependence

Analyzing equity market co-movements is important for risk diversification of an international portfolio. Copulas have several advantages compared to the linear correlation measure in modeling co-movement. This paper introduces a copula ARMA-GARCH model for analyzing the co-movement of international equity markets. The model is implemented with an ARMA-GARCH model for the marginal distributions and a copula for the joint distribution. After goodness of fit testing, we find that the Student’s t copula ARMA(1,1)-GARCH(1,1) model with fractional Gaussian noise is superior to alternative models investigated in our study where we model the simultaneous co-movement of nine international equity market indexes. This model is also suitable for capturing the long-range dependence and tail dependence observed in international equity markets. Rachev’s research was supported by grants from Division of Mathematical, Life and Physical Science, College of Letters and Science, University of California, Santa Barbara, and the Deutschen Forschungsgemeinschaft (DFG). Sun’s research was supported by grants from the Deutschen Forschungsgemeinschaft (DFG) and Chinese Government Award for Outstanding Ph.D Students Abroad 2006, No. 2006-180. Kalev’s research was supported with a NCG grant from the Faculty of Business and Economics, Monash University. Data are supplied by Securities Industry Research Center of Asia-Pacific (SIRCA) on behalf of Reuters. The constructive comments of two anonymous referees, the Associate Editor, A.S. Wirjanto, and the Editor-in-charge, Baldev Raj, are gratefully acknowledged. The reviewers and editors are not responsible for any residual errors and omissions.     

Quasi-Monte Carlo application in CGE systematic sensitivity analysis

The uncertainty and robustness of Computable General Equilibrium (CGE) models can be assessed by conducting a Systematic Sensitivity Analysis (SSA). Different methods have been used in the literature for SSA of CGE models such as Gaussian Quadrature and Monte Carlo methods. This article explores the use of Quasi-random Monte Carlo methods based on the Halton and Sobol’ sequences as means to improve the efficiency over regular Monte Carlo SSA, thus reducing the computational requirements of the SSA. The findings suggest that by using low-discrepancy sequences, the number of simulations required by the regular MC SSA methods can be notably reduced, hence lowering the computational time required for SSA of CGE models.     

无线传感器网络RSSI测距方法与精度分析

基于RSSI的测距技术是一项低成本的距离测量技术。分析了接收信号强度指示器(RSSI)多种 测距模型,结 合采用IEEE802.15.4协议的CC2430芯片,设计了测距实验,获取了多组数据,通过对实验数 据的分析,提出结合信标节点确定参数、高斯拟合确定测量值的RSSI测距处理方法。实验证 明,该方法能提高RSSI测距的抗干扰能力,20 m内节点间的测距精度能达到15 m 以下。     

Characterizing Gaussian Models of the Term Structure of Interest Rates

Models of the term structure of interest rates are considered for which, under the martingale measure, instantaneous forward rates are Gaussian. The possible forms of the covariance structure are characterized under appropriate formulations of the Markov property. It is demonstrated that imposing Markovian assumptions limits severely the covariances that may be obtained and that the strongest such formulation together with stationarity implies that the whole forward rate surface is necessarily a Gaussian random field described by just three parameters.